George Hedger1, Sarah L Rouse1,2, Jan Domański1, Matthieu Chavent1, Heidi Koldsø1,3, Mark S P Sansom1. 1. Department of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, U.K. 2. Department of Life Sciences, Imperial College London , London SW7 2AZ, U.K. 3. D. E. Shaw Research , 120 West 45th Street, 39th Floor, New York, New York 10036, United States.
Abstract
The exchange of ADP and ATP across the inner mitochondrial membrane is a fundamental cellular process. This exchange is facilitated by the adenine nucleotide translocase, the structure and function of which are critically dependent on the signature phospholipid of mitochondria, cardiolipin (CL). Here we employ multiscale molecular dynamics simulations to investigate CL interactions within a membrane environment. Using simulations at both coarse-grained and atomistic resolutions, we identify three CL binding sites on the translocase, in agreement with those seen in crystal structures and inferred from nuclear magnetic resonance measurements. Characterization of the free energy landscape for lateral lipid interaction via potential of mean force calculations demonstrates the strength of interaction compared to those of binding sites on other mitochondrial membrane proteins, as well as their selectivity for CL over other phospholipids. Extending the analysis to other members of the family, yeast Aac2p and mouse uncoupling protein 2, suggests a degree of conservation. Simulation of large patches of a model mitochondrial membrane containing multiple copies of the translocase shows that CL interactions persist in the presence of protein-protein interactions and suggests CL may mediate interactions between translocases. This study provides a key example of how computational microscopy may be used to shed light on regulatory lipid-protein interactions.
The exchange of ADP and ATP across the inner mitochondrial membrane is a fundamental cellular process. This exchange is facilitated by the adenine nucleotide translocase, the structure and function of which are critically dependent on the signature phospholipid of mitochondria, cardiolipin (CL). Here we employ multiscale molecular dynamics simulations to investigate CL interactions within a membrane environment. Using simulations at both coarse-grained and atomistic resolutions, we identify three CL binding sites on the translocase, in agreement with those seen in crystal structures and inferred from nuclear magnetic resonance measurements. Characterization of the free energy landscape for lateral lipid interaction via potential of mean force calculations demonstrates the strength of interaction compared to those of binding sites on other mitochondrial membrane proteins, as well as their selectivity for CL over other phospholipids. Extending the analysis to other members of the family, yeast Aac2p and mouse uncoupling protein 2, suggests a degree of conservation. Simulation of large patches of a model mitochondrial membrane containing multiple copies of the translocase shows that CL interactions persist in the presence of protein-protein interactions and suggests CL may mediate interactions between translocases. This study provides a key example of how computational microscopy may be used to shed light on regulatory lipid-protein interactions.
The mitochondrial
adenine nucleotide
translocase (ANT, also known as the ADP/ATP carrier, AAC) facilitates
export of ATP outward across the inner membrane into the cytoplasm,
in exchange for import of ADP back into the matrix.[1] This is driven by the electrochemical gradient across the
inner membrane. The translocase is one of the most abundant proteins
in the mitochondrial inner membrane.[2] Its
abundance and the importance of this transporter have rendered it
one of the best characterized members of the mitochondrial carrier
(MC) family, which facilitate the movement of a range of metabolites
in and out of mitochondria.[3]The
translocase has an intimate relationship with a key lipid in
mitochondrial membranes, cardiolipin (CL). The presence of CL is essential
for maximal stability of the translocase in vitro, and CL has been suggested to modulate interactions of ANT with
other proteins.[4,5] Knockdown of CL synthesis in humans
results in Sengers syndrome, a condition in which the carrier is depleted
from the inner membrane, leading to impaired oxidative phosphorylation
and symptoms ranging in severity from mild difficulties with exercise
to neo-natal fatality.[6,7]To date, atomic-resolution
structures of bovine and yeast forms
of ANT have been determined in a cytoplasm-facing state.[8,9] A nuclear magnetic resonance (NMR) structure has been determined
for another MC family member, uncoupling protein 2 (UCP2).[10] These translocase structures revealed a fold
in which six transmembrane helices (H1–H6) form a bundle around
a central substrate binding cavity, abutted on the matrix side by
three amphipathic helices (MH1–MH3) arranged around the outer
rim of the helix bundle (Figure ). There is an internal pseudo-3-fold symmetry, seen
also in the UCP2 structure, which sequence comparisons suggest to
be conserved across the MC family. The presence of CL was essential
for reconstitution and crystallization of ANT, and CL molecules have
been resolved in all crystal forms of the translocase, bound between
the short matrix helices. This agrees with earlier 31P
NMR measurements that indicated tight binding of CL molecules to bovine
heart translocase.[11] Although CL molecules
were not resolved in the structure of UCP2, the presence of this lipid
was essential to obtain interpretable spectra.[10]
Figure 1
ANT1 and CL. (A) Topology and structure of bovine ANT1 colored
to indicate the internal three-fold repeat symmetry. The structure
shown corresponds to the cytoplasm-facing state of ANT1 (Protein Data
Bank entry 1OKC).[8] (B) Coarse-grained (CG) representation
of ANT1 embedded in a lipid bilayer. (C) Atomistic and CG models of
CL.
ANT1 and CL. (A) Topology and structure of bovine ANT1 colored
to indicate the internal three-fold repeat symmetry. The structure
shown corresponds to the cytoplasm-facing state of ANT1 (Protein Data
Bank entry 1OKC).[8] (B) Coarse-grained (CG) representation
of ANT1 embedded in a lipid bilayer. (C) Atomistic and CG models of
CL.Despite the importance of CL in
the structure and function of the
ADP/ATP translocase and other MC family proteins, characterization
of these interactions within a membrane environment is relatively
scarce. Multiscale molecular dynamics simulations have proven to be
a powerful tool for identifying lipid binding sites[12] and for characterizing the energetics[13−15] and dynamics[16] of the interactions of the lipid with membrane
proteins. In this approach, simulations are applied at both coarse-grained
(CG) and atomistic resolutions.[17] In CG
simulations, the granularity of the system is decreased (Figure B,C), thus easing
the limitations on computationally accessible system sizes and time
scales inherent in atomistic simulations. This method has been used
to predict PIP2 lipid binding sites on Kir channels,[18] subsequently confirmed by crystal structures,[19,20] as well as to predict conserved lipid interaction patterns around
all aquaporins of known structure.[21] Coarse-graining
a system may also allow very large scale simulations of membrane patches
containing multiple copies of a given protein. Such simulations have
recently been used to define interactions of CL with the mitochondrial
respiratory chain complexes III and IV,[22] to determine interactions of lipids with GPCRs,[23] and to explore bacterial outer membrane protein diffusion
and oligomerization.[24]Here we apply
multiscale MD simulations to investigate the binding
of CL to ANT and to UCP2 in model mitochondrial membranes. We assess
structural, energetic, and dynamic aspects of lipid interactions with
a single copy of each protein, before evaluating the interplay of
protein–lipid and protein–protein interactions in large
scale simulations of membrane patches containing 25 copies of the
ANT molecule.
Methods
Coarse-Grained Simulations
All simulations were performed
using the GROMACS 4.6 (www.gromacs.org) simulation package[25] and the MARTINI
(http://md.chem.rug.nl/)
force field.[26−28] A summary of the simulations performed is provided
in Table .
Table 1
Overview of the Simulations Performed
description
membrane
composition
duration
1× bovine ANT1,a CG
outer leaflet, PC (100%)
5 × 6 μs
inner leaflet, PC (90%)/CL (10%)
1× bovine ANT1,a CG
outer leaflet, PC (50%)/PE (50%)
5 × 1 μs
inner leaflet, PC (42.5%)/PE (42.5%)/CL (15%)
1× yeast Aac2p,b CG
outer leaflet, PC (50%)/PE (50%)
5 × 1 μs
inner leaflet, PC (42.5%)/PE (42.5%)/CL (15%)
1× UCP2,c CG
outer leaflet, PC (50%)/PE (50%)
5 × 1 μs
inner leaflet, PC (42.5%)/PE (42.5%)/CL (15%)
PMF calculations, 1× ANT1,a CG
PC (100%)d
32 × 1–2 μs per PMF
25× bovine ANT1,a CG
outer leaflet, PC (60%)/PE (40%)
20 μs
inner leaflet, PC (50%)/PE (40%)/CL (10%)
25× bovine ANT1,a CG
outer leaflet, PC (60%)/PE (40%)
20 μs
inner leaflet, PC (60%)/PE (40%)
1× bovine ANT1,a AT
outer leaflet, PC (50%)/PE (50%)
0.5 μs
inner leaflet, PC (42.5%)/PE (42.5%)/CL (15%)
Simulation based on the crystal
structure of bovine ANT1 (PDB entry 1OKC(8)).
Simulation based on the crystal
structure of yeast Aac2p (PDB entry 4C9G(29)).
Simulation based on the crystal
structure of UCP2 (PDB entry 2LCK(10)).
See Potential
of Mean Force Calculations and Methods for further details regarding membrane composition.
Simulation based on the crystal
structure of bovine ANT1 (PDB entry 1OKC(8)).Simulation based on the crystal
structure of yeast Aac2p (PDB entry 4C9G(29)).Simulation based on the crystal
structure of UCP2 (PDB entry 2LCK(10)).See Potential
of Mean Force Calculations and Methods for further details regarding membrane composition.Protein Data Bank (PDB) coordinate
sets were processed using MemProtMD[30] to
remove cocrystallized lipids, waters, and
carboxyatractyloside inhibitors. CG simulations used the MARTINI version
2.1 force field.[27] Simulations of ANT utilized
an ElNeDyn elastic network.[31] Simulations
of UCP2 used an elastic network with a distance cutoff of 1 nm and
a force constant of 1000 kJ mol–1 nm–2. In addition, long distance PRE restraints (force constant of 1000
kJ mol–1 nm–2) were applied to
residues 68, 105, 202, and 205. The residues were chosen on the basis
of the NMR restraint file (PDB entry 2LCK) and were required to prevent collapse
of the UCP2 structure, as was also observed by Zoonens et al.[32] Each protein was placed in a box with dimensions
of 12 nm × 12 nm × 10 nm, containing 460 randomly oriented
PC lipids. The system was solvated using standard MARTINI water particles
and neutralized with ∼0.15 M NaCl. A 50 ns self-assembly simulation[33] was performed to allow formation of a lipid
bilayer around the protein. PC molecules within the bilayer were subsequently
exchanged with other lipid species to form an asymmetric bilayer of
specified lipid composition as described previously.[34] For repeat simulations, the lipids were independently exchanged
such that each repeat contained a different initial distribution of
lipid molecules consistent with the same specified lipid composition.
CL parameters were from ref (35). CL was modeled with a net ionization state of −2e (i.e., −1e per phosphate group)
based on experimental estimates.[36] The
acyl tails of PC and PE lipids were modeled as 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), while CL was modeled
as 1,3-bis(1-palmitoyl-2-oleoyl-sn-3-phosphatidyl)-sn-glycerol.Extended systems containing 25 copies
of the ANT1 molecule were
generated using the GROMACS genconf tool to concatenate
a system containing a single ANT1 molecule embedded in a PC bilayer
onto a 5 × 5 grid (Figure S1). The
lipids of the energy-minimized concatenated PC membrane were then
exchanged for a model mitochondrial membrane as described above.[34] The resultant system dimensions were 65 nm ×
65 nm × 14 nm, containing 25 proteins and ∼11000 lipids,
solvated by standard MARTINI water and neutralized by ∼0.15
M NaCl. The systems contained ∼4.7 × 105 particles.
An initial 1 μs equilibration period was used to facilitate
equilibration of lipid–protein interactions and facilitate
randomization of protein orientations. During this period, the backbone
particle of a single proline residue in each ANT1 molecule (Pro27)
was restrained in the X–Y plane, thus allowing rotation and randomization of protein orientations,
but preventing their translational movement. Systems both with and
without CL were then run for 20 μs of an unrestrained production
run simulation (see Table ).Simulations were performed under NPT conditions
at a temperature of 310 K and a pressure of 1 bar with periodic boundary
conditions. The temperature and semi-isotropic pressure were controlled
using the Berendsen thermostat and Berendsen barostat[37] with coupling constants of 4 ps. Equations of motion were
integrated using the leapfrog algorithm with a time step of 20 fs.
Electrostatics were modeled as reaction field with a Coulomb cutoff
of 1.2 nm, using a potential shift modifier. van der Waals interactions
were smoothly shifted off between 0.9 and 1.2 nm. The LINCS algorithm[38] was employed to constrain covalent bonds to
their equilibrium values.
Potential of Mean Force Calculations
PMFs were calculated
via umbrella sampling, utilizing a protocol previously described.[14] A 2 μs production run was performed with
bovine ANT1 (PDB entry 1OKC)[8] embedded in a PC bilayer
containing 10% CL within the inner leaflet. For each of the three
sites, a snapshot containing a bound CL/PC molecule was extracted.
A new PC bilayer was subsequently assembled around the position-restrained
(Fc = 1000 kJ mol–1 nm–2) protein and lipid of interest during a 50 ns self-assembly
simulation.[33] This simple composition was
chosen to accelerate convergence of calculations and has previously
been shown to cause no significant deviation compared to that for
protein–lipid PMFs conducted in two-component PC/PE bilayers.[22] A one-dimensional (1D) reaction coordinate ranging
from the lipid-bound state to the lipid-unbound state was then generated
via a steered MD (SMD) simulation. Each CL/PC/PS molecule was pulled
away from the protein over a distance of 3–4 nm at a rate of
0.1 nm/ns (Fc = 1000 kJ mol–1 nm–2). The force was applied to the GL0 headgroup
particle of CL, and the PO4 headgroup particle of PC/PS. Weak positional
restraints (Fc = 400 kJ mol–1 nm–2) were also applied in the X–Y plane to the backbone particle of each
proline residue within each of the three Px[D/E]xx[K/R] motifs of
the protein. Application of such restraints acted to prevent rotation
of the protein and translational “following” of the
tight binding CL molecules as they were pulled away. In addition,
weaker positional restraints (Fc = 50
kJ mol–1 nm–2) were applied to
the GL0/PO4 particle of the CL/PC lipid in the Y direction.
This served to retain the lipid on the 1D reaction coordinate and
thus enhance sampling of the chosen pathway. Snapshots spaced by ∼0.1
nm were extracted from the SMD simulation and used as input for umbrella
sampling simulations. Each window of the umbrella sampling was run
for 1–2 μs, with umbrella biasing potentials (Fc = 1000 kJ mol–1 nm–2) applied between the center of mass of the three restrained proline
residues and the GL0/PO4 particle of the CL/PC/PS lipid. Within umbrella
sampling simulations, long-range electrostatics were modeled using
particle mesh Ewald (PME).[39] The subject
lipid was treated separately from bulk lipids for temperature and
pressure coupling. Approximately 32 umbrella sampling simulations
were run per PMF. PMF profiles were constructed using the GROMACS
implementation (g_wham) of the weighted histogram analysis method
(WHAM).[40] Bayesian bootstrapping with 200
bootstraps was used to estimate the errors for each profile. Convergence
was assessed by comparing profiles calculated from independent 100
ns segments of simulation time (Figure S2), as well as by calculating profiles via replica exchange initiated
from different starting configurations. We previously tested the reproducibility
of this protocol and found well depths initiated from independent
repeats spanned a range of 5 kJ/mol (i.e., 2RT).[14] We tested this for the system presented here by conducting
two independent repeats of the entire calculation for site I, along
with two repeats utilizing different lateral lipid restraints (Figure S3). The well depths agreed to within
5 kJ/mol, suggesting this range is applicable to the current system
and indicating the robustness of the protocol to the choice of initial
snapshot and lipid restraint.
Atomistic Simulations
Atomistic simulations employed
the GROMOS96 53A6 force field.[41] A final
snapshot of a 1 μs CG simulation was converted to atomistic
detail using a fragment-based protocol.[42] The system was solvated using the SPC water model and neutralized
with ∼0.15 M NaCl. A 1 ns equilibration simulation was performed
with protein Cα particles restrained (Fc = 1000 kJ mol–1 nm–2).
This was followed by a 0.5 μs unrestrained simulation (see Table ). The temperature
was controlled at 310 K using a V-rescale thermostat[43] with a coupling constant τt of 0.1 ps.
Pressure was maintained at 1 bar using a Parrinello–Rahman
barostat[44] with a compressibility of 4.5
× 10–5 bar–1 and a coupling
constant τp of 1 ps. Electrostatic forces were modeled
using particle mesh Ewald (PME).[39] van
der Waals interactions were cut off at 1.2 nm. A time step of 2 fs
was employed, and covalent bond lengths were constrained using the
LINCS algorithm.[38]
Analysis and Visualization
Two-dimensional (2D) density
maps for lipids and proteins were calculated as described previously.[24] Three-dimensional (3D) lipid density isosurfaces
were computed using the VolMap plugin of VMD.[45] Diffusion coefficients were extracted from the mean square displacement
(MSD) using g_msd and a time period of 20 ns. Contact and protein
clustering analysis was performed using in-house scripts and MDAnalysis.[46] Lipid contacts were calculated between each
residue of the protein and the headgroup particle of CL (defined by
GL0) using a cutoff of 0.6 nm to define a contact. A cutoff of 4.4
nm between protein centers of mass was used for protein clustering
analysis, while per residue protein–protein contacts were calculated
utilizing the approach described in ref (24). The VMD[45] software
package was used for visualization of simulation data.
Results
Identification
of CL Binding Sites on Bovine ANT1
A
CG molecular model of bovine ANT1 was embedded into a simple model
membrane containing PC (90%) and CL (10%) in the matrix-facing leaflet,
and PC (100%) in the cytoplasm-facing leaflet. This CL content lies
within the range estimated for mitochondrial inner membranes from
lipidomics.[47−49] Five repeat simulations of bovine ANT1 were conducted,
each with a duration of 6 μs and beginning from a different
distribution of lipids within the bilayer (see Table and Methods for
details).CL molecules were seen to encounter and bind to three
specific sites on the protein [sites I–III (Figure and Movie S1)]. Each site was composed of a groove on the protein surface
formed by the N-terminal end of the even-numbered transmembrane helices
(H2, H4, and H6) of each repeat, and the short amphipathic matrix
helices (MH1–MH3). The location of the sites thus has a symmetry
related to the internal three-fold structural repeat. The location
of these sites is in excellent agreement with those identified in
X-ray crystal structures.[8,9] This indicates that
the sites occupied in the crystal structure persist within a membrane
environment. Interactions were predominantly mediated by the headgroup
moieties of CL, as seen in the time-averaged 2D density maps for CL
(Figure B). In contrast,
the acyl tails exhibited more dynamic interactions, which resulted
in less well-defined density, though a small degree of ordering was
seen at site III. This is consistent with a number of crystal structures
in which only the headgroup moieties and adjacent atoms of the acyl
chains were resolved.[29] The dominance of
headgroup interactions seen here is also consistent with functional
assays performed in yeast showing Aac2p assembles normally regardless
of the acyl chain composition of CL.[50]
Figure 2
CL binding
sites on bovine ANT1. (A) In the left panel, the initial
simulated system consisted of a single molecule of bovine ANT1 embedded
in a mixed PC (lime) and CL (magenta) bilayer, solvated with standard
MARTINI water particles (transparent surface) and neutralized with
∼0.15 M NaCl (blue spheres). The right panel is the final snapshot
of a 6 μs simulation showing three bound CL molecules (magenta).
(B) Time-averaged 2D density maps of CL in the membrane plane for
the headgroup (left) and acyl tail moieties (right). (C) View onto
the base of the translocase from the matrix showing the positioning
of the three CL (magenta) binding sites around the protein within
the X-ray structure (left) and CG simulations (right). The CL binding
sites within the CG simulations are shown by the time-averaged probability
density surface for the CL molecules, contoured to show the three
binding sites. The density surface was calculated from 5 × 6
μs simulation repeats, each starting from a different random
lipid distribution. See Figure S4 for per
simulation density maps.
CL binding
sites on bovine ANT1. (A) In the left panel, the initial
simulated system consisted of a single molecule of bovine ANT1 embedded
in a mixed PC (lime) and CL (magenta) bilayer, solvated with standard
MARTINI water particles (transparent surface) and neutralized with
∼0.15 M NaCl (blue spheres). The right panel is the final snapshot
of a 6 μs simulation showing three bound CL molecules (magenta).
(B) Time-averaged 2D density maps of CL in the membrane plane for
the headgroup (left) and acyl tail moieties (right). (C) View onto
the base of the translocase from the matrix showing the positioning
of the three CL (magenta) binding sites around the protein within
the X-ray structure (left) and CG simulations (right). The CL binding
sites within the CG simulations are shown by the time-averaged probability
density surface for the CL molecules, contoured to show the three
binding sites. The density surface was calculated from 5 × 6
μs simulation repeats, each starting from a different random
lipid distribution. See Figure S4 for per
simulation density maps.The number of contacts formed between each residue of the
protein
and the CL headgroup was calculated over the course of each simulation.
Within each site, the CL headgroup showed a preference for interaction
with the N-termini of the even-numbered TM helices and matrix helices.
In site I, the highest degree of contact was seen with S68, G72, T154,
and G155. Residues showing high levels of contact in site II were
Q174, G175, G252, and T253, while in site III, they were G52, I53,
G272, and W274 (Figure A). A number of the interacting residues form part of the highly
conserved [YWF][RK]G and [YF]xG motifs,[2] respectively, located at the N-termini of the even-numbered TM helices
and matrix helices (Figure B). In particular, the glycine residues within these motifs
were seen to form frequent contacts with CL in the simulations. The
colocalization of CL interactions to these conserved sequence motifs
is encouraging, given also the suggested role of the glycine residues[2] within the motifs in mediating CL interactions
within crystal structures.[9] PC lipids showed
comparatively less specificity for these regions (Figure S5). To assess the robustness of the results to the
presence of PE lipids (present in vivo(47)) and changes in CL concentration, 5 × 1
μs simulations were conducted in mixed membranes with a composition
of PC (50%) and PE (50%) in the cytoplasm-facing leaflet and PC (42.5%),
PE (42.5%), and CL (15%) in the matrix-facing leaflet. The simulations
yielded very similar patterns of contact of CL with the PC/CL only
membranes, suggesting the interaction is not sensitive to the presence
of PE (Figure C),
as has been seen for the interactions of CL with other mitochondrial
proteins.[22]
Figure 3
Interactions of CL with
bovine ANT1. (A) Normalized average frequency
of CL headgroup contacts per residue. Residues within each of the
even-numbered helices (H2, H4, and H6) and the matrix helices (MH1–MH3)
exhibiting the highest degree of contact are labeled (see Methods for full details of contact analysis). (B)
Lateral view into each CL binding site with the backbone trace of
the protein colored by the relative extent of contacts formed with
CL, from white (no contact) to magenta (high contact). Insets show
the corresponding view onto the whole translocase colored according
to a three-fold repeat topology. The positions of the conserved motifs
are labeled. (C) Normalized average frequency of phospholipid headgroup
contacts per residue, for the lipid species within three-component
membranes.
Interactions of CL with
bovine ANT1. (A) Normalized average frequency
of CL headgroup contacts per residue. Residues within each of the
even-numbered helices (H2, H4, and H6) and the matrix helices (MH1–MH3)
exhibiting the highest degree of contact are labeled (see Methods for full details of contact analysis). (B)
Lateral view into each CL binding site with the backbone trace of
the protein colored by the relative extent of contacts formed with
CL, from white (no contact) to magenta (high contact). Insets show
the corresponding view onto the whole translocase colored according
to a three-fold repeat topology. The positions of the conserved motifs
are labeled. (C) Normalized average frequency of phospholipid headgroup
contacts per residue, for the lipid species within three-component
membranes.To further assess interactions
within the identified binding sites,
a CG snapshot of ANT1 was converted[42] to
atomistic detail and simulated for 0.5 μs. Sites I and II of
the chosen snapshot were occupied by CL molecules, while site III
was unoccupied, thus allowing us both to test the stability of bound
CL molecules and to explore possible atomistic binding events within
the same extended simulation. Calculation of the Cα root-mean-square
deviation (RMSD) during the simulation revealed a stable value of
∼0.3 nm for the core structural elements (i.e., helices) and
∼0.4 nm for all residues, indicating that, despite the absence
of the carboxyatractyloside inhibitor, the apo-cytoplasm-facing structure
is conformationally stable on the time scale simulated (Figure S6). The CL molecules within sites I and
II remained bound (Figure ), with the phosphate moieties contacting those conserved
motifs seen to form frequent contacts in the CG simulations. In contrast,
the acyl chain tails exhibited more dynamic interactions and adopted
a range of conformations (Figure S6,B).
Of interest within site I, the side chain of R71 remained pointing
downward, consistent with its position within crystal structures (Figure B).[9] No lipid binding events were observed at site III, despite
one CL being positioned in the vicinity of the site. This suggests
longer time scales may be required to capture the full process of
lipid binding at atomistic resolution.
Figure 4
Atomistic simulation
of bovine ANT1. (A) The left panel is a view
from the matrix side, with the phosphate particles of the bound CL
molecules shown as spheres. For each phosphate particle, 1000 evenly
distributed snapshots are shown over the 0.5 μs simulation,
colored according to simulation time. This may be compared to the
phosphate distribution (right) for a noninteracting bulk CL. (B) Final
snapshot of site I showing the arrangement of conserved motifs (gray),
N-terminal ends of the helices (green and cyan), and CL (magenta).
Atomistic simulation
of bovine ANT1. (A) The left panel is a view
from the matrix side, with the phosphate particles of the bound CL
molecules shown as spheres. For each phosphate particle, 1000 evenly
distributed snapshots are shown over the 0.5 μs simulation,
colored according to simulation time. This may be compared to the
phosphate distribution (right) for a noninteracting bulk CL. (B) Final
snapshot of site I showing the arrangement of conserved motifs (gray),
N-terminal ends of the helices (green and cyan), and CL (magenta).
Energetics of CL Binding
To assess the strength and
selectivity of CL interactions, we calculated a potential of mean
force (PMF) for the CL–ANT1 interaction via CG simulation and
umbrella sampling. The PMF (or free energy profile) between two species
describes the change in free energy along a particular reaction coordinate
and is calculated from the probability distribution of the two species
along that coordinate.[51] This approach
has recently been used to define the binding of CL to mitochondrial
respiratory chain complexes III and IV[22,52] and to characterize
lipid interactions of the epidermal growth factor receptor (EGFR)
transmembrane domain.[14] For each of the
three sites, a steered MD simulation was conducted in which a force
was applied to pull the CL molecule out of its binding site into the
bulk membrane along a 1D reaction coordinate (r)
perpendicular to the protein surface in the plane of the bilayer (Figure A). The free energy
profile along this coordinate was then calculated via umbrella sampling,
with r defined as the distance between the center
of mass of three conserved prolines within ANT1 and the β-glycerol
moiety of CL.
Figure 5
Potentials of mean force for binding of the lipid to ANT1.
(A)
View onto the base of ANT1 illustrating the reaction coordinates used
in free energy calculations. ANT1 is colored according to its three-fold
repeat topology, with the position of each binding site indicated
by the time-averaged probability density isosurfaces for CL phosphates
(magenta). The arrows indicate the approximate 1D reaction coordinates
along which the PMF was calculated. (B) PMF profiles for interactions
of CL (magenta) and PC (black) with each of the three binding sites,
and a control non-CL binding region. For site I, a PMF profile was
also calculated for a further anionic lipid species, PS (green). The
standard deviations estimated from bootstrapping[40] are shown as the shaded area behind each curve.
Potentials of mean force for binding of the lipid to ANT1.
(A)
View onto the base of ANT1 illustrating the reaction coordinates used
in free energy calculations. ANT1 is colored according to its three-fold
repeat topology, with the position of each binding site indicated
by the time-averaged probability density isosurfaces for CL phosphates
(magenta). The arrows indicate the approximate 1D reaction coordinates
along which the PMF was calculated. (B) PMF profiles for interactions
of CL (magenta) and PC (black) with each of the three binding sites,
and a control non-CL binding region. For site I, a PMF profile was
also calculated for a further anionic lipid species, PS (green). The
standard deviations estimated from bootstrapping[40] are shown as the shaded area behind each curve.The profiles revealed comparable tight binding
of CL molecules
to each of the three sites, with well depths of approximately −20
kJ/mol (Figure B).
In contrast, pulling a CL molecule away from a region not predicted
to bind CL revealed a well depth of approximately −4 kJ/mol,
indicating no significant interaction in this region. Conducting the
same calculations for zwitterionic PC lipids showed no significant
interaction of this species beyond the value of RT (2.5 kJ/mol), demonstrating
the marked selectivity of these sites for CL over zwitterionic phospholipids.
These values may be compared to those obtained for cytochrome c oxidase (CIV) via the same method,[15] revealing that the binding sites on bovine ANT1
have an affinity for CL higher than those of most of the sites on
CIV, other than for two high-affinity sites on CIV that are estimated to bind with an interaction free energy of approximately
−32 kJ/mol. Interestingly, calculation of the PMF profile for
a second anionic lipid species, phosphatidylserine (PS), at site I
revealed a well depth of approximately −15 kJ/mol, i.e., intermediate
between those of CL and PC. Although the abundance of PS[47] within the inner mitochondrial membrane is comparatively
low, these calculations suggest the capacity of the binding sites
to interact with other anionic lipid species, albeit less favorably
than with CL.
Conservation of Binding Sites
The
strong binding of
CL to bovine ANT1 together with the structural conservation[53] of the internal three-fold repeat of mitochondrial
carriers suggests that these sites are likely to be conserved over
other members of the family. We tested this by running CG simulations
of yeast Aac2p and mouse UCP2. Multiple (5 × 1 μs) simulations
were run for Aac2p and UCP2 in the same manner as they were for ANT1
(Table ). Analysis
of the average probability distribution of CL over the course of the
simulations showed preferential localization to the three equivalent
sites seen for ANT1 (Figure ). These positions compare well with the multiple crystal
structures of bovine ANT1[8,9] and yeast Aac2p and
Aac3p.[29] The simulations are supportive
of direct interactions of CL with UCP2 and predict that these interactions
occur at sites equivalent to those seen in ANT1 and Aac2p.
Figure 6
Conservation
of CL binding sites. (A) Location of cocrystallized
lipids (magenta) in bovine ANT1 (PDB entry 1OKC)[8] and yeast
Aac2p (PDB entry 4C9G).[29] (B) CL binding sites identified by
CG–MD simulations. The magenta surface shows the probability
density for the CL headgroup phosphate particles around a snapshot
of each protein, contoured to indicate the positions of the phosphate
moieties of CL within each site. (C) Normalized average number of
CL headgroup contacts per residue within simulations of bovine ANT1,
yeast Aac2p, and mouse UCP2.
Conservation
of CL binding sites. (A) Location of cocrystallized
lipids (magenta) in bovine ANT1 (PDB entry 1OKC)[8] and yeast
Aac2p (PDB entry 4C9G).[29] (B) CL binding sites identified by
CG–MD simulations. The magenta surface shows the probability
density for the CL headgroup phosphate particles around a snapshot
of each protein, contoured to indicate the positions of the phosphate
moieties of CL within each site. (C) Normalized average number of
CL headgroup contacts per residue within simulations of bovine ANT1,
yeast Aac2p, and mouse UCP2.Analysis of lipid contacts formed in the yeast Aac2p and
UCP2 simulations
showed patterns spatially similar to those of bovine ANT1 (Figure C), despite differences
in sequence and the somewhat “looser” packing of the
transmembrane helices in the UCP2 structure. This suggests the groovelike
architecture of the sites is also an important contributor to CL binding,
and that a degree of sequence substitution may be tolerated. The conservation
of these sites within both crystals (obtained in the presence of detergent)
and a simulated membrane environment along with their presence in
three MC proteins is supportive of both their biological significance
and their likely conservation in other members of the family.
Lipid
Interactions and Organization of Bovine ANT1 in Large
Membrane Patches
Large scale simulations of membrane patches
containing multiple protein copies have recently proven to be useful
in understanding the dynamic organization of lipids and proteins.[54] In light of this, a single molecule of bovine
ANT1 embedded in a small membrane patch was replicated (Figure S1) to create a large membrane patch with
25 ANT1 molecules in an ∼65 nm × 65 nm area of membrane
containing ∼11000 lipid molecules (see Table ), with a cytoplasm-facing leaflet containing
PC (60%)/PE (40%) and a matrix leaflet containing PC (50%), PE (40%),
and CL (10%). This composition lies within the range estimated for
the inner mitochondrial membrane from lipidomics.[47,55] This membrane was used as the basis of 20 μs of unrestrained
molecular dynamics.Examination of the final snapshot showed
a degree of protein oligomerization (Figure A), with a mixture of monomers, dimers, and
higher-order oligomers observed. Analysis of the dynamics of protein
clustering showed the self-assembly of oligomers began on a submicrosecond
time scale (Figure B and Movie 2), with ∼50% of the
proteins participating in an oligomeric state by 8 μs. Calculation
of the averaged 2D protein density maps for ANT1 and CL showed that
this interaction occurred at three specific interaction interfaces,
which colocalized with the three CL binding sites identified previously
(Figure C). Indeed,
visual inspection of the simulations showed that CL molecules were
often found at these interfaces, loosely bridging proteins. However,
in contrast to the crystallographic dimers,[29] we did not observe a stable arrangement in which two CL molecules
were present between the two proteins. Such an arrangement may be
unfavorable because of the proximity of the negatively charged (−2e) CL headgroups, as well as a degree of steric conflict.
This is suggestive of possible competition between protein–protein
and protein–lipid interactions. Calculation of 2D density maps
and ANT-CL contacts for the first 1 μs of the simulation (during
which period the ANT molecules are predominantly monomeric) and the
final 1 μs (during which period the ANT molecules are predominantly
oligomeric) revealed similar profiles, indicating the broad patterns
of CL interaction remain similar under the two regimes (Figure S7). However, further simulations with
improved sampling and resolution would be needed to unpack any finer
details of CL behavior within oligomers.
Figure 7
Organization of bovine
ANT1 in large membrane patches. (A) Final
snapshot (t = 20 μs) of the matrix leaflet
showing the organization of 25 ANT1 proteins in a PC/PE/CL mixed membrane.
(B) Clustering dynamics shown as the percentage of ANT1 cluster size
over the simulated time course, along with a snapshot of an ANT1 dimer
with CL mediating the interaction. Other lipid molecules have been
omitted for the sake of clarity. (C) Density plots showing the frequency
of occurrence of ANT around ANT, and CL around ANT. The protein has
been omitted from the CL plot for the sake of clarity.
Organization of bovine
ANT1 in large membrane patches. (A) Final
snapshot (t = 20 μs) of the matrix leaflet
showing the organization of 25 ANT1 proteins in a PC/PE/CL mixed membrane.
(B) Clustering dynamics shown as the percentage of ANT1 cluster size
over the simulated time course, along with a snapshot of an ANT1 dimer
with CL mediating the interaction. Other lipid molecules have been
omitted for the sake of clarity. (C) Density plots showing the frequency
of occurrence of ANT around ANT, and CL around ANT. The protein has
been omitted from the CL plot for the sake of clarity.The interfaces at sites I and II showed a stronger
preference for
protein–protein interaction, with comparatively weaker density
seen at site III. However, we did not observe a clear preference for
certain permutations of protein–protein interaction interfaces,
but rather a mixture of interfaces were seen. For example, the interface
at site I was able to interact with all other interfaces. For all
regions, the contact area between interacting proteins was relatively
small, with contacts to neighboring protein molecules seen almost
exclusively at the cytoplasm-facing ends of the TM helices, and the
short matrix helices (Figure S8). Residues
exposed to the core of the membrane on the concave surface of the
translocase formed comparatively few direct protein–protein
contacts, in keeping with the “hourglass” shape of ANT1.
Contacts of this hydrophobic surface were instead mediated by lipid
tails.Interestingly, simulating a comparably sized membrane
patch without
CL in the bilayer (Table ) resulted in a greater degree of oligomerization of the ANT
population over the 20 μs time course (Figure S9). This suggests that CL may have the capacity to modulate
the oligomerization process. Calculation of diffusion coefficients
for the ANT1 protein molecules showed values comparable to those seen
for GPCRs[23] and did not exhibit a significant
difference in the presence and absence of CL (Figure S9). This suggests the difference in oligomerization
is unlikely to be due to differences in diffusive behavior in the
two lipid mixtures and may instead be indicative of modulation via
direct interaction.
Discussion
Cardiolipin molecules
have been observed bound to several crystal
forms of the bovine ANT1.[8,9] Three CL molecules are
bound per ANT1 monomer, with the phosphate groups positioned within
grooves formed by the short matrix helices. The sites identified within
our simulations are in complete agreement with the experimentally
determined sites, demonstrating that the latter persist within a membrane
environment and thus are likely to be present in vivo. Calculation of free energy profiles for lateral lipid interaction
with these sites shows moderately tight binding of CL molecules compared
to other regions on the protein, along with clear selectivity for
CL over zwitterionic phospholipids, in agreement with indications
from 31P NMR measurements.[11] The well depths for these profiles are −20 to −25
kJ/mol and may be compared to profiles calculated via the same method
for other protein–lipid interactions, including interactions
of glycolipid and phosphoinositide with the EGFR,[14] binding of phosphoinositide to PH domains,[13] and in particular interactions of CL with mitochondrial
CIII and CIV.[22,52] This overall
suggests the sites on bovine ANT1 have a clear affinity for CL, which
is greater than that of the majority of CL binding sites on CIV, and is superseded by only two particularly high-affinity
sites on CIV that exhibit interaction free energies of
approximately −32 kJ/mol.[15]Extending the simulations to the two other members of the mitochondrial
carrier family of known structure, yeast Aac2p and mouse UCP2, revealed
comparable direct interaction of CL with both proteins and demonstrated
conservation of binding site location. For yeast Aac2p, this agrees
well with the location of cocrystallized CL molecules.[29] At present, there are no structural data for
binding of CL to UCP2. However, the presence of CL was required to
obtain usable NMR spectra, suggestive of direct interaction.[10] Our simulations support this and predict CL
to bind directly to three sites on UCP2 equivalent to those seen in
ANT1 and Aac2p. Interestingly, recent biochemical work[56] on the related protein, UCP1, suggested a binding
stoichiometry of three CL molecules per monomer, in support of our
simulation-based prediction for UCP2. The conservation in binding
site location over several proteins suggested by simulation, structural
and biochemical studies, and the predicted conservation of the internal
three-fold repeat is strongly indicative of likely conservation of
the CL binding sites in other members of the mitochondrial carrier
family. It will be interesting to see how far this conservation extends
as further structures emerge.Advances in simulation methodology[12,57] allow access
to extended time and length scales. We were thus able to investigate
the larger (∼0.1 μm) scale organization and protein–lipid
interactions of bovine ANT1. These simulations suggest the cytoplasm-facing
conformation of bovine ANT1 has the capacity to form self-interactions
at specific interfaces and thus to form oligomers within model membranes.
The protein–protein interfaces colocalize with the CL binding
sites, and CL is often seen to bridge between adjacent proteins. However,
in contrast to crystallographic dimers,[9] we did not observe a stable arrangement in which two CL molecules
may be present at an interface, with the interfaces rather being mediated
by a single CL. This may be related to the unfavorable electrostatics
of having two negatively charged (−2e each[58]) CL headgroups in the proximity, in a membrane
environment that allows for protein–protein and protein–lipid
assemblies more dynamic and transient than what may be observed in
a crystal. It would therefore be attractive to analyze the relative
free energies of the different modes of protein–protein and
protein–CL–protein interactions observed within these
dynamic complexes. However, this would be likely to require the development
of more effective simulation-based sampling regimes before such free
energies may be reliably estimated.[59] Interestingly,
simulations of membrane patches in the absence of CL showed a greater
degree of oligomerization over the 20 μs simulation compared
to the membrane with CL present. This suggests a more complex relationship
between CL and ANT–ANT interactions, with a single CL molecule
bound between interfaces that can mediate protein interactions as
a molecular glue,[60] but the presence of
two CL molecules between interfaces possibly acting as a block to
disfavor oligomerization.The oligomeric state of ANT1 has been
much debated.[4,61,62] While the functional unit of
the translocase is widely accepted to be monomeric, this does not
preclude oligomerization under certain conditions. It is important
to remember that our observations pertain to the cytoplasm-facing
state of the translocase within simple model membranes: both conformational
changes and biologically complex lipid mixtures may also influence
oligomerization, as observed for GPCRs.[23,63] In particular,
other anionic lipids, e.g., PS, PA, and PI, at low levels in the inner
mitochondrial membrane[47−49] may interact with ANT within living cells. Other in vivo factors such as the high degree of membrane curvature
of the mitochondrial inner membrane, along with a more heterogeneous
protein population, may also influence ANT–ANT interactions.
We note that a number of in vitro model membrane
studies have suggested CL may regulate the activity of certain proteins
via modulation of curvature and other biophysical properties of the
inner membrane.[64−67] Larger scale simulations capable of assessing such macroscopic properties
would be of interest in this regard. Likewise, we note that key inner
membrane-resident compounds such as electron-transferring quinones
have been suggested to influence membrane properties.[68] Structural data for a number of other mitochondrial membrane
proteins are now available, along with EM data on their in
vivo arrangement and membrane curvature.[69] As the number of lipid parameters and time and length scales
accessible to simulations continue to increase,[54] it may be possible to address these factors in large scale
simulations. With regard to mechanistic insights into the influence
of CL on the ANT transport cycle, as information about the possible
nature of ANT conformational states continues to emerge,[2,70] a key extension of the current simulations would be to examine the
differential interactions of CL with multiple conformational states
of ANT to reveal the detailed mechanism of the influence of CL on
ANT function.
Methodological Considerations
It is important to be
aware of possible limitations in the simulation methods employed.
Use of CG models results in an inherent loss of chemical detail, which
may be expected to influence the accuracy of protein–lipid
interactions. Although the ionization state of the CL headgroup has
been estimated to be −2e in solution,[36] it is possible this may change depending on
the microenvironment, as may protein ionization states. Capturing
such effects would require constant-pH simulations, with a concomitant
increase in computational load.[71] Despite
the absence of such effects, good agreement is seen between our CG
and atomistic simulations, together with previously resolved crystal
structures. In addition, we note the method has previously been shown
to correctly predict lipid binding sites on an increasing number of
other membrane proteins,[19,21,52] in agreement with experiment,[12] and is
capable of predicting the effects of mutation on lipid binding.[13,14]A further key limitation of current simulations is the accessible
time scale, which remains a challenge even when using CG models. This
is particularly pertinent for large systems containing multiple copies
of proteins. These limitations may impede the investigation of slowly
converging system properties such as protein–protein interactions.[22,23] In the current study of a 20 μs time scale, we capture only
part of the self-assembly process, and an equilibrated state for protein–protein
interactions has likely not been reached. Thus, insights into the
strength of protein–protein interactions are circumscribed
because of limited statistics for association and dissociation events.
Nonetheless, important information can be gleaned in identifying protein
interaction interfaces and the influence of lipids on the process,
as seen for, e.g., respiratory complexes III and IV,[22] and for the S1P1 receptor.[23]With regard to protein–protein interactions, the MARTINI
model has been suggested to overestimate interaction strengths in
aqueous solutions.[72] However, within a
membrane environment, the model performs well, with the free energy
profiles for glycophorin A transmembrane helix dimerization estimated
to be approximately −30 to −40 kJ/mol in MARTINI CG,[73,74] and −45 to −60 kJ/mol in all-atom simulations,[75,76] which agree reasonably with available experimental data.[77] The application of MARTINI dihedral restraints
together with an ElNeDyn elastic network[31] prohibits conformational transitions, and thus, we consider only
the cytoplasm-facing state of the translocase, for which crystal structures
are known. One might anticipate that potential conformational transitions[70] within the protein could influence lateral protein–protein
interactions as well as protein–CL interactions.
Conclusions
In summary, we have characterized three CL binding sites on the
cytoplasm-facing conformation of bovine ANT1 within model mitochondrial
membranes. Free energy calculations reveal the ∼100 μM
affinity of these sites for CL, and their selectivity over zwitterionic
phospholipids. Equivalent sites are present for mouse UCP2 and yeast
Aac2p, indicative of both their biological significance and conservation
within the transporter family, as further supported by recent biochemical
studies of UCP1.[56] Simulations in extended
membrane patches demonstrate that CL interactions at these sites persist
in the presence of protein–protein interactions, and indeed,
CL molecules may mediate interactions between adjacent ANT1 molecules,
permitting formation of a range of oligomeric states. More generally,
our simulations demonstrate further the ability of computer simulations
to identify lipid binding sites on membrane protein, providing near-atomic-resolution
characterization of protein–lipid interactions to complement
biochemical and structural studies.
Authors: Siewert J Marrink; H Jelger Risselada; Serge Yefimov; D Peter Tieleman; Alex H de Vries Journal: J Phys Chem B Date: 2007-06-15 Impact factor: 2.991
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